Search ga_ls8c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2016-12-06 10:09:03	ga_ls8c_ard_3-2-1_099066_2016-12-06_final
2021-11-18 10:09:03	ga_ls8c_ard_3-2-1_099066_2021-11-18_final
2022-07-21 10:28:22	ga_ls8c_ard_3-2-1_102068_2022-07-21_final
2022-07-28 10:39:49	ga_ls8c_ard_3-2-1_103081_2022-07-28_final
2022-08-15 10:28:00	ga_ls8c_ard_3-2-1_101082_2022-08-15_final
2022-08-27 09:13:51	ga_ls8c_ard_3-2-1_089082_2022-08-26_final
2022-08-28 11:36:00	ga_ls8c_ard_3-2-1_112082_2022-08-28_final
2022-09-07 10:33:26	ga_ls8c_ard_3-2-1_102080_2022-09-07_final
2022-09-09 10:21:29	ga_ls8c_ard_3-2-1_100081_2022-09-09_final
2022-09-19 09:18:32	ga_ls8c_ard_3-2-1_090078_2022-09-18_final
2022-09-22 11:30:44	ga_ls8c_ard_3-2-1_111084_2022-09-22_final
2022-10-02 10:24:31	ga_ls8c_ard_3-2-1_101073_2022-10-02_final
2022-10-02 10:24:55	ga_ls8c_ard_3-2-1_101074_2022-10-02_final
2022-10-07 10:41:01	ga_ls8c_ard_3-2-1_104068_2022-10-07_final
2022-10-13 10:03:27	ga_ls8c_ard_3-2-1_098067_2022-10-13_final
2022-10-21 09:23:16	ga_ls8c_ard_3-2-1_090090_2022-10-20_final
2022-10-30 09:12:45	ga_ls8c_ard_3-2-1_089079_2022-10-29_final
2022-10-30 10:50:03	ga_ls8c_ard_3-2-1_105075_2022-10-30_final
2022-10-31 11:32:55	ga_ls8c_ard_3-2-1_112074_2022-10-31_final
2022-11-05 10:13:22	ga_ls8c_ard_3-2-1_099076_2022-11-05_final
2022-11-05 11:53:03	ga_ls8c_ard_3-2-1_115078_2022-11-05_final
2022-11-13 11:00:45	ga_ls8c_ard_3-2-1_107071_2022-11-13_final
2022-11-22 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-11-21_final
2022-12-08 09:21:38	ga_ls8c_ard_3-2-1_090086_2022-12-07_final
2022-12-08 10:56:32	ga_ls8c_ard_3-2-1_106076_2022-12-08_final
2022-12-11 11:26:37	ga_ls8c_ard_3-2-1_111074_2022-12-11_final
2022-12-17 10:49:52	ga_ls8c_ard_3-2-1_105075_2022-12-17_final
2022-12-19 10:34:41	ga_ls8c_ard_3-2-1_103068_2022-12-19_final
2022-12-31 11:05:22	ga_ls8c_ard_3-2-1_107083_2022-12-31_final
2023-01-03 09:58:11	ga_ls8c_ard_3-2-1_096085_2023-01-03_final
2023-01-09 10:54:47	ga_ls8c_ard_3-2-1_106072_2023-01-09_final
2023-01-12 09:46:46	ga_ls8c_ard_3-2-1_095072_2023-01-12_final
2023-01-19 11:36:33	ga_ls8c_ard_3-2-1_112084_2023-01-19_final
2023-01-26 09:57:08	ga_ls8c_ard_3-2-1_097067_2023-01-26_final
2023-01-26 11:38:49	ga_ls8c_ard_3-2-1_113074_2023-01-26_final
2023-02-13 11:26:22	ga_ls8c_ard_3-2-1_111074_2023-02-13_final
2023-02-17 11:01:36	ga_ls8c_ard_3-2-1_107074_2023-02-17_final
2023-02-19 10:50:00	ga_ls8c_ard_3-2-1_105076_2023-02-19_final
2023-02-24 11:10:01	ga_ls8c_ard_3-2-1_108080_2023-02-24_final
2023-03-23 10:49:39	ga_ls8c_ard_3-2-1_105076_2023-03-23_final
2023-03-25 10:34:29	ga_ls8c_ard_3-2-1_103069_2023-03-25_final
2023-03-28 09:32:28	ga_ls8c_ard_3-2-1_092084_2023-03-28_final
2023-03-30 09:20:29	ga_ls8c_ard_3-2-1_090085_2023-03-29_final
2023-04-04 11:13:51	ga_ls8c_ard_3-2-1_109075_2023-04-04_final
2023-04-07 10:06:36	ga_ls8c_ard_3-2-1_098077_2023-04-07_final
2023-04-09 09:51:48	ga_ls8c_ard_3-2-1_096071_2023-04-09_final
2023-04-09 11:31:52	ga_ls8c_ard_3-2-1_112074_2023-04-09_final
2023-04-11 09:39:47	ga_ls8c_ard_3-2-1_094072_2023-04-11_final
2023-04-11 11:19:28	ga_ls8c_ard_3-2-1_110074_2023-04-11_final
2023-04-14 11:52:45	ga_ls8c_ard_3-2-1_115080_2023-04-14_final
2023-04-15 10:53:08	ga_ls8c_ard_3-2-1_106070_2023-04-15_final
2023-04-24 10:49:19	ga_ls8c_ard_3-2-1_105076_2023-04-24_final
2023-04-25 11:31:23	ga_ls8c_ard_3-2-1_112073_2023-04-25_final
2023-04-27 09:44:31	ga_ls8c_ard_3-2-1_094084_2023-04-27_final
2023-05-17 09:21:33	ga_ls8c_ard_3-2-1_090089_2023-05-16_final
2023-06-02 09:21:12	ga_ls8c_ard_3-2-1_090088_2023-06-01_final
2023-06-03 11:41:46	ga_ls8c_ard_3-2-1_113084_2023-06-03_final
2023-06-10 10:06:22	ga_ls8c_ard_3-2-1_098077_2023-06-10_final
2023-07-05 11:40:54	ga_ls8c_ard_3-2-1_113081_2023-07-05_final
2023-07-10 10:16:36	ga_ls8c_ard_3-2-1_100071_2023-07-10_final
2023-07-13 10:49:30	ga_ls8c_ard_3-2-1_105076_2023-07-13_final
2023-07-17 10:26:47	ga_ls8c_ard_3-2-1_101081_2023-07-17_final
2023-07-29 10:46:25	ga_ls8c_ard_3-2-1_105068_2023-07-29_final
2023-08-03 11:10:35	ga_ls8c_ard_3-2-1_108082_2023-08-03_final
2023-08-04 10:08:59	ga_ls8c_ard_3-2-1_099067_2023-08-04_final
2023-08-06 09:57:26	ga_ls8c_ard_3-2-1_097069_2023-08-06_final
2023-08-21 09:21:04	ga_ls8c_ard_3-2-1_090086_2023-08-20_final
2023-09-06 10:55:33	ga_ls8c_ard_3-2-1_106075_2023-09-06_final
2023-09-14 10:03:00	ga_ls8c_ard_3-2-1_098067_2023-09-14_final
2023-09-21 10:11:12	ga_ls8c_ard_3-2-1_099072_2023-09-21_final
2023-09-24 09:06:49	ga_ls8c_ard_3-2-1_088081_2023-09-23_final
2023-10-06 09:32:46	ga_ls8c_ard_3-2-1_092084_2023-10-06_final
2023-10-16 10:03:54	ga_ls8c_ard_3-2-1_098069_2023-10-16_final
2023-10-16 10:07:30	ga_ls8c_ard_3-2-1_098078_2023-10-16_final
2023-10-17 10:49:33	ga_ls8c_ard_3-2-1_105075_2023-10-17_final
2023-10-31 09:28:41	ga_ls8c_ard_3-2-1_091089_2023-10-30_final
2023-11-08 11:51:21	ga_ls8c_ard_3-2-1_115075_2023-11-08_final
2023-11-14 09:35:25	ga_ls8c_ard_3-2-1_093075_2023-11-14_final
2023-11-14 11:14:18	ga_ls8c_ard_3-2-1_109075_2023-11-14_final
2023-11-18 10:46:50	ga_ls8c_ard_3-2-1_105068_2023-11-18_final
2023-11-30 11:11:57	ga_ls8c_ard_3-2-1_109069_2023-11-30_final
2023-12-02 09:23:28	ga_ls8c_ard_3-2-1_091076_2023-12-01_final
2023-12-02 09:25:51	ga_ls8c_ard_3-2-1_091082_2023-12-01_final
2023-12-03 10:07:06	ga_ls8c_ard_3-2-1_098077_2023-12-03_final
2023-12-03 11:44:47	ga_ls8c_ard_3-2-1_114074_2023-12-03_final
2023-12-04 09:13:04	ga_ls8c_ard_3-2-1_089081_2023-12-03_final
2023-12-04 10:49:09	ga_ls8c_ard_3-2-1_105074_2023-12-04_final
2023-12-05 09:57:30	ga_ls8c_ard_3-2-1_096084_2023-12-05_final
2023-12-11 09:22:02	ga_ls8c_ard_3-2-1_090088_2023-12-10_final
2023-12-12 09:58:31	ga_ls8c_ard_3-2-1_097071_2023-12-12_final
2023-12-17 10:22:18	ga_ls8c_ard_3-2-1_100084_2023-12-17_final
2024-01-08 11:18:24	ga_ls8c_ard_3-2-1_110070_2024-01-08_final
2024-01-15 11:25:01	ga_ls8c_ard_3-2-1_111071_2024-01-15_final
2024-01-30 10:41:40	ga_ls8c_ard_3-2-1_104071_2024-01-30_final
2024-02-11 09:30:21	ga_ls8c_ard_3-2-1_092078_2024-02-11_final
2024-02-17 10:33:19	ga_ls8c_ard_3-2-1_102081_2024-02-17_final
2024-02-29 09:22:16	ga_ls8c_ard_3-2-1_090089_2024-02-28_final
2024-02-29 10:54:22	ga_ls8c_ard_3-2-1_106072_2024-02-29_final
2024-03-06 10:17:35	ga_ls8c_ard_3-2-1_100073_2024-03-06_final
2024-03-06 11:57:40	ga_ls8c_ard_3-2-1_116076_2024-03-06_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years